Mohamed I University

ABSTRACT We present an analysis that investigates the $H_0$ and $S_8$ tensions by considering a dark energy model. The latter is a late-time model characterized by a future abrupt event known as the Little Rip (LR) model and characterized by one extra parameter, $\beta$, compared to the standard model, $\Lambda$CDM. To test this approach, we perform a statistical analysis by the MCMC method using the most recent observational data. We obtain a positive correlation in ($H_0$, $\beta$) plane. We also note that the Hubble tension is less than $3\sigma$ when using early measurements, i.e. cosmic microwave background (CMB) data, and when combining it with baryon acoustic oscillation (BAO) data, but it is no longer so when we combine early and late measurements [i.e. PantheonPlus (PP)]. In addition, we test the model with DESI-DR2 combined with CMB and recent SNIa measurements. We notice that our model shifts toward the quintessence field. For a complete statistical analysis, we use the Akaike Information Criteria and Bayesian analysis of the evidence. According to Bayes factors, we find that the LR model provides an improved fit only to CMB data.

Accurate estimation of daily reference evapotranspiration (ETo) is essential for effective irrigation scheduling, improved water-use efficiency, and sustainable crop production in arid and semi-arid regions. Although the FAO-56 Penman–Monteith equation (ETo PM ) is widely accepted as the reference method, its reliance on complete meteorological data limits its applicability in data-scarce agricultural systems such as those in eastern Morocco. This study proposes a practical solution for daily ETo estimation under data-limited conditions by evaluating machine learning approaches against traditional empirical models. Daily climatic data (2001–2025) were collected from airport meteorological stations, NASA POWER reanalysis, and on-farm sensors at four representative locations in Eastern Morocco (Oujda, Berkane, Taourirt, and Figuig). ETo was computed using the ETo PM equation. Three ML algorithms—Support Vector Regression (SVR), Random Forest (RF), and Extreme Gradient Boosting (XGBoost)—were developed under multiple input scenarios guided by feature-importance analysis, which identified solar radiation (Rsn), maximum temperature (Tmax), and relative humidity (RH) as dominant predictors. To ensure realistic evaluation and avoid information leakage, a strict chronological split was applied, using 2001–2018 for training and 2019–2025 for independent testing. The best ML configurations were then compared with widely used empirical ETo equations (Hargreaves–Samani, Jensen–Haise, Priestley–Taylor, Makkink, and Turc). Results showed that XGBoost consistently outperformed SVR and RF, achieving the best balance between accuracy and computational efficiency. The three-input configuration (Rsn + Tmax + RH) produced near-reference performance across all locations ( R 2 = 0.976; RMSE < 0.55 mm day −1 ; training time ≈ 4.48 s; RAM ≈ 0.13 MB), while the reduced two-input configuration (Rsn + Tmax) maintained reliable performance ( R 2 = 0.936; RMSE ≈ 0.60 mm day −1 ; training time ≈ 0.33 s; RAM ≈ 0.13 MB). In contrast, empirical approaches exhibited poor predictive capability and weak transferability, with negative R 2 values and substantially larger errors (RMSE generally > 4 mm day −1 , exceeding 7 mm day −1 in the weakest formulations). Overall, this machine learning–based framework provides a robust and operational alternative for daily ETo estimation in eastern Morocco, supporting efficient irrigation scheduling, improved agricultural water management, enhanced crop productivity, and sustainable agriculture in arid and semi-arid regions.

The Rif’s belt is characterized by low to moderate seismic activity resulting from the continental collision between the African and Eurasian plates. This seismic activity, which involves devastation and human losses, requires an in-depth study of its origins and mechanisms. This study aims to identify the geological structures responsible for seismic activity in the eastern Rif by adopting an integrated methodological approach. The methodology relies on the use of a Geographic Information System (GIS) to process and analyze multiple geological, seismological, and geophysical datasets. Various filters were applied to magnetic and gravimetric data (vertical derivatives) to characterize the subsurface. The analysis of earthquake focal mechanisms helped identify active faults. The results show that the seismicity, with a NW-SE orientation, is localized within a fragile depression south of the city of Selouane. The final geological model highlights a system of faults and strike-slips oriented NE-SW and NW-SE. A significant spatial correlation is observed between epicenters and Messinian-aged NW-SE strike-slips, suggesting their reactivation. The analysis indicates that a system of dextral strike-slips is likely the source of this seismic activity. The proposed geodynamic model represents a major advancement in understanding local seismic activities and serves as an essential reference for future studies. These results significantly contribute to the assessment and management of seismic risks, thereby enhancing the safety and resilience of populations in this high-risk area.KEYWORDS: Geodynamic model; Seismotectonic; Focal mechanism; Magnetic; Gravimetric; ·Eastern Rif.

Abstract This paper presents the system identification and validation of Synchronous Buck Converter (SBC) models using both white-box and black-box approaches. The white-box method employs difference equations derived from continuous state-space models, while the black-box approach estimates second-order state-space representations. Models are experimentally validated against laboratory measurements, with accuracy quantified using the Normalized Root Mean Square Error (NRMSE). By analysing the trade-off between model fidelity and real-time feasibility, the study identifies the most accurate model for reliable real-time simulation and controller development.

The article "Problems of the Epistemological Reference of the Arabic Linguistic Achievement in Algeria: Selected Models" attempts to understand this linguistic achievement in terms of its limits and forms, questioning this achievement, "modern Algerian linguistic composition," with the aim of revealing its epistemological (cognitive) origins. Undoubtedly, Algerian linguistic models suggest diversity and multiplicity, but at the same time, they pose questions such as: What are their theoretical foundations and epistemological origins? What are the conditions of science and knowledge that governed their formulation and modeling? How were their linguistic models constructed, if indeed they were constructed? Perhaps these questions and others fall directly within a purely epistemological field, which is concerned not only with linguistic structures and semantic analyses, but also with the scientific conditions upon which they are based and the references and theoretical foundations to which they refer.

Fusarium oxysporum f. sp. albedinis (Foa) is a destructive soil-borne fungal pathogen responsible for bayoud disease, which threatens date palm cultivation in North Africa. This disease has caused significant agricultural losses, particularly in Morocco, where the Zagora oasis is a key region for date palm production. Within this oasis, two cultivars—Black Bousthammi and Jihel—are mainly cultivated and exhibit complete resistance and high susceptibility to Foa, respectively. Thus, this study aimed to identify and compare the bacterial and fungal communities associated with the two cultivars and understand their assemblage regarding the disease resistance or susceptibility. Moreover, we explored the influence of each cultivar on the composition and structure of its root-associated microbiome and examined its relationship with the microbial populations present in the surrounding bulk soil, to better understand the recruitment dynamics that shape the microbiome in the roots. The results revealed significant differences in microbiome composition between the bulk soil and roots of the two date palm cultivars, and between the microbiome of the resistant and susceptible cultivars as well. Moreover, we observed that date palm cultivars had a greater effect on bacterial community composition than on fungal population. Interestingly, the susceptible cultivar exhibited a higher enrichment of several beneficial genera, such as Pseudomonas, Lysinibacillus, Actinomadura, Halomonas, Kocuria, Serratia, Phyllobacterium, Bacillus, Streptomyces, and Trichoderma. The presence of these beneficial genera, known for their antagonistic activity against phytopathogens, may reflect a recruitment pattern associated with pathogen pressure in the susceptible cultivar. This study is the first to compare the microbial communities between a bayoud-resistant and susceptible cultivar and provides insights into the potential role of the root microbiome when plants are under pathogen pressure. This reinforces the need to further elucidate the genetic and biological mechanisms that trigger microbiome assembly, which could be a key step in developing effective methods to manage the bayoud disease.

Rhabdomyolysis is a serious clinical condition often associated with serious complications and can be life-threatening in nature. The following is a case report of a healthy 17-year-old male adolescent who presented with rhabdomyolysis due to a dual hit of Influenza A and excessive physical exertion. Acute onset of myalgia, weakness in the lower extremities, and dark urine warranted his hospitalization in the intensive care unit for critical monitoring and investigation. The laboratory findings indicated a high creatine kinase level of more than 60,000 U/L, severe metabolic acidosis, hyperkalemia, and renal failure. Despite aggressive fluid resuscitation, persistent anuria and metabolic derangements warranted renal replacement therapy with continuous veno-venous hemofiltration followed by intermittent hemodialysis, resulting in progressive recovery of renal function and clinical improvement. This case highlights the importance of recognizing rhabdomyolysis in patients presenting with acute neuromuscular symptoms after febrile illness and strenuous exercise, emphasizing the need for early diagnosis and prompt supportive management to prevent irreversible renal injury.